Comprehensive Summary
Wolber et al. examines the implementation of total-body photography (TBP) to track the development of [malignant] pigmented lesions. This innovative advancement enables physicians to analyze and contrast body maps across time, which holds important implications for those who are higher risk for melanoma. The research was conducted by gathering participants “from the intervention arm of a randomized controlled trial” (Wolber et al., 2024). These 145 participants were from Queensland, Australia, and the participants had been monitored by the researchers for two years with the use of 3D TBP to detect any new lesions that formed over those two years. The researchers were able to uncover 56 participants who had presented with 119 new lesions (during this time). Melanoma was detected after excising 4 of these lesions. Upon histopathologic analysis, the Breslow Depth was relatively shallow, suggesting the lesions may have been caught (and stopped) early in their tracks. Importantly, these lesions did not meet the diagnostic criteria for biopsy upon dermoscopic analysis. These findings, taken as a whole, support the utility of TBP in the early detection of otherwise benign- presenting lesions.
Outcomes and Implications
The research presented by Wolber and co-authors suggests the importance of the integration of “machine-learning support” (Wolber et al., 2024) to create a more streamlined, accurate, and effective way of detecting skin cancer. This work uniquely and fruitfully applies to the field of medicine because it allows for physicians to easily utilize this machine learning in a clinical setting, allowing for a more accurate and reliable diagnosis of skin cancers. In order to ensure that we can reliably detect malignant lesions, widespread implementation of this TBP technology across a variety of clinical settings is recommended.